Wearable congestive heart failure management system

ABSTRACT

A non-invasive, wearable and portable medical device for evaluation and monitoring the heart condition for patients with congestive heart failure and a CHF management system is provided comprising a wearable textile-based device utilizing physiologic and biometric sensors, a Signal Acquisition Unit, and a monitoring system executing a suite of software algorithms to monitor and evaluate patients with CHF.

This application is a continuation of U.S. application Ser. No.15/967,792, filed May 1, 2018, which claims the benefit of U.S.Provisional Patent Application No. 62/500,085, filed May 2, 2017,entitled WEARABLE CONGESTIVE HEART FAILURE MANAGEMENT SYSTEM, the entiredisclosures of which are hereby incorporated by reference.

FIELD OF INVENTION

The present invention relates to the field of non-invasive, wearable andportable medical devices, methods, systems and apparatus, including butnot limited, for monitoring physiological parameters.

BACKGROUND

Congestive Heart Failure (CHF) is a complex clinical syndrome thatresults from any structural or functional impairment of the ventricularchamber of the heart that affects the filling or ejection of blood in acardiac cycle. CHF manifests clinically as fatigue and dyspnea(shortness of breath). This may in turn result in exercise intoleranceand fluid retention. Fluid retention leads to pulmonary congestionand/or peripheral edema. Cardiac rhythm abnormalities are very commonamong CHF patients. Any new abnormalities that arise in a patient withfluid decompensation prolongs hospitalization as well as increasesmortality rates.

Within 5 years of a CHF diagnosis, the mortality rate is 50%. The 30day, 1-year and 5-year fatality rates after CHF related hospitalizationwere 10.4%, 22% and 42.3% respectively. Post discharge mortalityincreased from 4.3% to 6.4% between 1993 and 2005. In 2006, the numberof deaths with a mention of CHF was as high as it was in 1995. One outof every nine mortalities in the US has CHF mentioned as a cause. CHFrelated deaths are approximately 7% of all cardiovascular diseases. Inthe US, CHF related costs exceeded $30 billion in 2013. The average costper patient for CHF related hospitalization was $23,077. Hospitalizationafter a CHF diagnosis happens at least once in 83% of the patients andup to four times in 43% of the patients. See C. W. Yancy, M. Jessup, B.Bozkurt, J. Butler, D. E. Casey Jr, M. H. Drazner, et al., “2013ACCF/AHA Guideline for the Management of Heart Failure: A Report of theAmerican College of Cardiology Foundation/American Heart AssociationTask Force on Practice Guidelines,” Journal of the American College ofCardiology, vol. 62, pp. e147-e239, Oct. 15, 2013.

The current diagnostic tests and monitoring methods for CHF are limitedin terms of: the need for hospitalization, in-home monitoring,obtrusiveness, and invasiveness. The common evaluation methods arecategorized into: laboratory tests, imaging studies, and additionalstudies based on patient history.

The laboratory tests include: Complete blood count (CBC), which mayindicate anemia or infection as potential causes of heart failure,Urinalysis (UA), which may reveal proteinuria, which is associated withcardiovascular disease, Serum electrolyte levels, which may be abnormalowing to causes such as fluid retention or renal dysfunction, Blood ureanitrogen (BUN) and creatinine levels, which may indicate decreased renalblood flow, Fasting blood glucose levels, because elevated levelsindicate a significantly increased risk for heart failure (diabetic andnondiabetic patients), Liver function tests (LFTs), which may showelevated liver enzyme levels and indicate liver dysfunction due to heartfailure, B-type natriuretic peptide (BNP) and N-terminal pro-B-type(NT-proBNP) natriuretic peptide levels, which are increased in heartfailure; these measurements are closely correlated with the NYHA heartfailure classification, Electrocardiogram (ECG) (12-lead), which mayreveal arrhythmias, ischemia/infarction, and coronary artery disease aspossible causes of heart failure.

The imaging studies include: Chest radiography (posterior-anterior,lateral), which may show pulmonary congestion, an enlarged cardiacsilhouette, or other potential causes of the patient's symptoms, 2-Dechocardiographic and Doppler flow ultrasonographic studies, which mayreveal ventricular dysfunction and/or valvular abnormalities (PinamontiB, Di Lenarda A, Sinagra G, Camerini F. Restrictive left ventricularfilling pattern in dilated cardiomyopathy assessed by Dopplerechocardiography: clinical, echocardiographic and hemodynamiccorrelations and prognostic implications. Heart Muscle Disease StudyGroup. J Am CollCardiol. 1993 Sep. 22(3):808-15, and Temporelli P L,Scapellato F, Eleuteri E, Imparato A, Giannuzzi P. Dopplerechocardiography in advanced systolic heart failure: a noninvasivealternative to Swan-Ganz catheter. Circ Heart Fail. 2010 May.3(3):387-94), Coronary arteriography in patients with a history ofexertional angina or suspected ischemic LV (left ventricular)dysfunction, which may reveal coronary artery disease, Maximal exercisetesting with/without respiratory gas exchange and/or blood oxygensaturation, which assesses cardiac and pulmonary function with activity,the inability to walk more than short distances, and a decreased peakoxygen consumption reflect more severe disease.

Other additional studies based on the patient history include: Screeningfor hemochromatosis, in which iron overload affects cardiac function,screening for sleep-disturbed breathing, which affects neurohormonalactivation, screening for human immunodeficiency virus (HIV), which mayresult in heart failure from possible direct infectious effects, fromdisease treatment effects causing CAD, or from other causes, Testing forrheumatologic diseases, amyloidosis, or pheochromocytoma, all of whichmay cause cardiomyopathy, serum and urine electrophoresis forlight-chain disease, Genetic testing for at-risk patients with afirst-degree relative who has been diagnosed with a cardiomyopathyleading to heart failure, which may aid in detecting early disease onsetand guide treatment (see Murphy R T, Starling R C. Genetics andcardiomyopathy: where are we now?, Cleve Clin J Med. 2005 Jun.72(6):465-6, 469-70, 472-3 passim, and Lindenfeld J, Albert N M, BoehmerJ P, Collins S P, Ezekowitz J A, Givertz M M, et al. HFSA 2010Comprehensive Heart Failure Practice Guideline. J Card Fail. 2010 Jun.16(6):e1-194); and holter monitoring, which may reveal arrhythmias orabnormal electrical activity (e.g., in patients with heart failure and ahistory of MI (Myocardial Infarction) who are being considered forelectrophysiological study to document ventricular tachycardia [VT]inducibility). See [Guideline] Dickstein K, Cohen-Solal A, Filippatos G,et al. for the Task Force for the Diagnosis and Treatment of Acute andChronic Heart Failure 2008 of the European Society of Cardiology. ESCGuidelines for the diagnosis and treatment of acute and chronic heartfailure 2008: the Task Force for the Diagnosis and Treatment of Acuteand Chronic Heart Failure 2008 of the European Society of Cardiology.Developed in collaboration with the Heart Failure Association of the ESC(HFA) and endorsed by the European Society of Intensive Care Medicine(ESICM). Eur Heart J. 2008 Oct. 29(19):2388-442. [Medline], and[Guideline] Lindenfeld J, Albert N M, Boehmer J P, et al, for the HeartFailure Society of America. Executive summary: HFSA 2010 comprehensiveheart failure practice guideline. J Card Fail. 2010 Jun. 16(6):e1-194.)

Unobtrusive health monitoring is highly beneficial for maintaininghealth and independence of high risk and chronic disease patients.Intelligent wearable sensor systems with simple installation, minimalmaintenance and user involvement can be the best method for ubiquitoushealth monitoring.

Wearable sensor systems in form of smart clothing can contributetremendously to self-defined and autonomous (at home) living withimproved quality of life. They are cost effective and providelightweight simple technical infrastructure. Existing ambulatoryrecording equipment rely on conventional silver-silver chloride(Ag—AgCl) gel electrodes to perform long term monitoring. Such gel-basedelectrodes cannot be adapted to clothing as reusable sensors. Plainconductive textile-based electrodes do not form a good quality contactand are susceptible to ambient noise.

Nanostructured textile-based dry sensors and electrodes are bettersuited for long term non-invasive monitoring and measurement ofphysiological parameters with low baseline noise, because of theirimproved sensitivity and ability to perform adequately with the naturalmoisture level of skin. See Pratyush Rai, Sechang Oh, PrashanthShyamkumar, Mouli Ramasamy, Robert E. Harbaugh and Vijay K. Varadan,“Nano-Bio-Textile Sensors with Mobile Wireless Platform for WearableHealth Monitoring of Neurological and Cardiovascular Disorders,” J.Electrochem. Soc. 2014 volume 161, issue 2, B3116-B3150. Thesetextile-based sensors can be seamlessly integrated into garments ofdaily use such as vests and brassieres. In combination with state of theart embedded wireless network devices that can communicate with a smartphone, a laptop, or directly to a remote server through the mobilenetwork (GSM, 4G LTE, GPRS) (see US Pre-Grant Pub. No. 2013/0281815 A1),they can function as wearable wireless health diagnostic systems thatare more intuitive to use.

SUMMARY OF THE INVENTION

However, existing non-invasive CHF monitoring devices are not capable ofperforming a multi-parametric, continuous, remote patient monitoring. Inthis regard, these conventional systems lack the ability to perform longterm monitoring, non-reusability, lack a scalable and standardizedwireless communication platform for internet-based health care servicesand lack adequate user-friendly design paradigms that would accommodatepatients who are not technically trained.

In accordance with a first embodiment of the present invention, awearable textile-based harness includes an adjustable elastic horizontalband and an adjustable elastic vertical band. The horizontal band wrapsproximate to a body portion around the thoracic cage region and thehorizontal band passes over the xyphoid process and thoracic cagebetween 5th and 6th ribs positions. The vertical band wraps over theshoulder passing between shoulder muscle and deltoid muscle. Thevertical band and horizontal band connected in front at the xyphoidprocess location and at the back on either side of the back-center. Afirst plurality of sensors are located along a first vector extendingalong the vertical band on a front side of the harness, wherein thefirst plurality of sensors include a first and second sensor locatedalong the first vector above the heart of the wearer and a third andfourth sensor located along the first vector below the heart of thewearer, the second sensor being located downward of the first sensor andthe fourth sensor located downward of the third sensor. A secondplurality of sensors are located along a second vector extending alongthe horizontal band on the front side of the harness, wherein the secondplurality of sensors include a fifth and sixth sensor located along thesecond vector to the right of the heart of the wearer and a seventh andeighth sensor located along the second vector to the left of the heartof the wearer, the sixth sensor being located downward of the fifthsensor and the eighth sensor located downward of the seventh sensor.Upon wearing the textile-based harness, the first and second pluralityof sensors are placed in contact with skin of wearer, preferably with asensor-skin pressure in the range of 60 to 250 gram-force. Theadjustable elastic horizontal and vertical bands may be adjustable viafasteners.

In accordance with other variants of the first embodiment, the elastichorizontal band and the elastic vertical band are made of an elasticfabric, each of the first and second plurality of sensors are located atsensor locations on the elastic fabric, and at one or more of the sensorlocations, a non-elastic material is fixed on the elastic fabric, anelastomeric material is fixed on the non-elastic material, and one ormore of the sensors is fixed on the elastomeric material.

In accordance with other variants of the first embodiment, the first andsecond plurality of sensors include at least one textile basednanosensor comprising vertically standing nanofilaments. The sensors mayalso include a heart sound sensor and/or an IMU.

In accordance with a second embodiment of the present invention, a CHFmanagement system includes a wearable textile-based harness and a signalacquisition unit.

The wearable textile-based harness includes an elastic horizontal bandand an elastic vertical band. The horizontal band wraps proximate to abody portion around the thoracic cage region and the horizontal bandpasses over the xyphoid process and thoracic cage between 5th and 6thribs positions. The vertical band wraps over the shoulder passingbetween shoulder muscle and deltoid muscle. The vertical band andhorizontal band connected in front at the xyphoid process location andat the back on either side of the back-center. A first plurality ofsensors located along a first vector extending along the vertical bandon a front side of the harness. A second plurality of sensors locatedalong a second vector extending along the horizontal band on the frontside of the harness. Upon wearing the textile-based harness, the firstand second plurality of sensors are placed in contact with skin ofwearer, preferably with a sensor-skin pressure in the range of 60 to 250gram-force.

The signal acquisition unit includes an analog front end circuit, aprocessor, a wireless module, and a power supply, the SAU receivingsignals from the plurality of sensors, generating, from the signals, anECG signal and an ICG signal, and wirelessly transmitting at least theECG signal and the ICG signal to a remote computing device.

In accordance with other variants of the second embodiment, the harnessmay include some or all of the features described above with respect tothe first embodiment.

In accordance with other variants of the second embodiment, the ECGsignal includes a first ECG signal from the first vector and a secondECG signal from the second vector, and the ICG signal includes a firstICG signal from the first vector and a second ICG signal from the secondvector.

In accordance with other variants of the second embodiment, the systemfurther comprises the remote computing device, the remote computingdevice including a processor and computer readable media having storedthereon computer executable process steps operative to control theprocessor to display on a display screen a graph of the first ECG signalfrom the first vector as a function of time, a graph of the first ICGsignal from the first vector as a function of time, a graph of thesecond ECG signal from the second vector as a function of time and agraph of the second ICG signal from the second vector as a function oftime.

In accordance with other variants of the second embodiment, the firstplurality of sensors located along the first vector further comprises aheart sound sensor, wherein the signal acquisition unit furthergenerates a heart sound signal and wirelessly transmits the heart soundsignal to the remote computing device, and the remote computing deviceincludes computer executable process steps operative to control theprocessor to display on a display screen a graph of the heart soundsignal as a function of time.

In accordance with a third embodiment of the present invention a methodof monitoring cardiovascular health in a human, comprises providing awearable textile-based harness

The harness includes an elastic horizontal band and an elastic verticalband wherein, when worn by the human, the horizontal band wrapsproximate to a body portion of the human around the thoracic cageregion, the horizontal band passing over the xyphoid process andthoracic cage between 5th and 6th ribs positions, the vertical bandwrapping over a shoulder of the human and passing between the shouldermuscle and deltoid muscle, and extending diagonally downward towards thea xyphoid process location, wherein the vertical band and horizontalband are connected in front at the xyphoid process location and at theback on either side of the back-center. A first plurality of sensorslocated along a first vector extending along the vertical band on afront side of the harness and a second plurality of sensors locatedalong a second vector extending along the horizontal band on the frontside of the harness. Upon wearing the textile-based harness, the firstand second plurality of sensors are placed in contact with skin ofwearer.

The method further includes generating, from the first and secondplurality of sensors, at least one ECG vector signal, and at least oneICG vector signal.

In accordance with other variants of the third embodiment, the at leastone ECG vector signal includes a first ECG signal from the first vectorand a second ECG signal from the second vector, and the at least one ICGvector signal includes a first ICG signal from the first vector and asecond ICG signal from the second vector.

In accordance with other variants of the third embodiment, the methodfurther comprises displaying on a display screen a graph of the firstECG signal from the first vector as a function of time, a graph of thefirst ICG signal from the first vector as a function of time, a graph ofthe second ECG signal from the second vector as a function of time and agraph of the second ICG signal from the second vector as a function oftime.

In accordance with other variants of the third embodiment, the methodfurther comprises generating a plurality of parameters from the ECG andICG vectors, including: Atrial electrical activity from at least one ofthe ECG vectors; Ventricular electrical activity from at least one ofthe ECG vectors; PR interval of atrio-ventricular conduction intervalfrom at least one of the ECG vectors; QRS measures from at least one ofthe ECG vectors; ST-T measures from at least one of the ECG vectors;Cardiac output from at least one of the ICG vectors; Stroke volume fromat least one of the ICG vectors; Cardio-vascular pressures from at leastone of the ICG vectors; Pulmonary pressures from at least one of the ICGvectors; Minute ventilation from at least one of the ICG vectors;Shortness of breath from at least one of the ICG vectors; Exercisetolerance from at least one of the ECG and ICG vectors; Heart rate fromat least one of the ECG vectors; Heart rhythm from at least one of theECG vectors; Transthoracic impedance from at least one of the ICGvectors; and Ejection fraction from at least one of the ICG/ECG vectors.

In accordance with other variants of the third embodiment, the methodfurther comprises generating a composite CHF monitoring metric based ondata received from the first and second plurality of sensors.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1(a) and 1(b) show a front and rear view of an exemplary wearabletextile-based harness model made of an elastomeric fabric material withvertical band attached to one side of the back center.

FIGS. 1(c) and 1(d) show a front and rear view of an exemplary wearabletextile-based harness model made of an elastomeric fabric material withvertical band attached to the other side of the back center.

FIG. 2(a) shows a load-elongation curve of the elastomeric materialshown in FIG. 1.

FIG. 2(b) is a graph which shows optimal force vs. harness locationbased on activity.

FIG. 2(c) is an illustration of the harness showing five regions.

FIGS. 3(a) and (b) illustrate a portion of the harness of FIG. 1(a,b)having a sensor location where the harness is augmented with anelastomeric material and a rigid material to provide protrusion forbetter skin-sensor contact.

FIGS. 4(a) and 4(b) show exemplary sensor locations along the body andICG vector configurations for the harness of FIG. 1(a) and FIG. 1(b).

FIG. 5 shows an exemplary data plot showing two vectors of ECG, twovectors of ICG, heart sound, respiration, and actigraphy.

FIG. 6 shows the measured acceleration on three axes for detectingactivity and posture.

FIG. 7(a) shows a substrate for an exemplary sensor system on a textilebased wearable substrate used for detection of ICG, ECG, respirationrate, heart sound and actigraphy.

FIG. 7(b) shows circuitry for an exemplary sensor system on a textilebased wearable substrate used for detection of ICG, ECG, respirationrate, heart sound and actigraphy.

FIG. 7(c) shows an oval shaped substrate for an exemplary sensor systemon a textile based wearable substrate used for detection of ICG, ECG,respiration rate, heart sound and actigraphy.

FIG. 7(d) shows a clover-leaf shaped substrate having nanostructuresthereon for an exemplary sensor system on a textile based wearablesubstrate used for detection of ICG, ECG, respiration rate, heart soundand actigraphy

FIG. 8 illustrates an exemplary data flow of the CHF management system.

FIG. 9 is an exemplary block diagram for the SAU.

FIG. 10(a)-(b) are flow charts which illustrate the operation of thevarious software modules that make up the Web services that manage andpresent the data in a user interface.

FIG. 11 shows an exemplary composite data packet for transmitting datafrom a plurality of channels having different sampling rates.

FIG. 12 shows an exemplary login page for a physician on the web portal602.

FIG. 13 shows an exemplary landing page for the physician on web portal602.

FIGS. 14(a), 14(b) and 14(c) show an exemplary sequence of userinterfaces that the physician would encounter as part of the sequence ofsteps following to initiate monitoring CHF for a new patient on webportal 602.

FIGS. 15(a), 15(b), and 15(c) show an exemplary sequence of screens thatare used by a medical professional to setup a patient's smart phone formonitoring of CHF through the SAU (Signal Acquisition Unit).

FIG. 16 shows an exemplary user interface for a patient who launches theapp after monitoring setup is completed.

FIGS. 17(a) and 17(b) show an exemplary User interface on smart phonefor a patient-initiated recording on the SAU.

FIGS. 18(a) and 18(b) show an exemplary User interface wherein data isuploaded from the smart phone 401 to the database services 603.

FIG. 19 shows an exemplary user interface implemented on web portal 602that displays all the data acquired by the SAU as plots.

FIG. 20 shows an exemplary user interface for the display of a compositeCHF status monitoring metric that is derived from the parameters inTable 1.

FIG. 21 shows an exemplary user interface wherein the physician canspecify alert thresholds for various parameters that are captured by theSAU and computed by step 605 of FIG. 10(a).

DETAILED DESCRIPTION OF THE EMBODIMENTS

The present invention relates to a non-invasive, wearable and portablemedical device for evaluation and monitoring the heart condition forpatients with CHF. More particularly, the invention relates to a systemincluding a wearable device utilizing physiologic and biometric sensors,a Signal Acquisition Unit (SAU), and a monitoring system executing asuite of software algorithms to monitor and evaluate patients withCongestive Heart Failure (CHF). More particularly, the system measuresphysiological parameters including: one or more vectors of ECG, one ormore vectors of ICG, impedance (Z0), respiration, heart sounds, andactigraphy and postures.

In particular, the wearable device may be made of an elastomeric harnesscomprising of active and passive nanosensors, heart sound sensor, anInertial Measurement Unit (IMU), and a connector to electrically connectthe aforementioned sensors to the SAU. The SAU may be comprised of anAnalog Front End circuit (AFE), a processing unit, a storage unit, apower supply, and a wireless module.

The monitoring system may include one or more processors executingsoftware that includes a suite of algorithms to monitor, evaluate CHFand heart condition for people already diagnosed with CHF. Moreparticularly, the monitoring system is operable to perform algorithmicparametric extraction of data received from the wearable device from theSAU. The algorithmic parametric extraction includes, but is not limitedto, extracting: atrial electrical activity, ventricular electricalactivity, ECG rhythm analysis, PR interval or atrio-ventricularconduction interval, patient activity score, posture, cardiac output,stroke volume, relative tidal volume, cardio-vascular pressures, patientgeographic location and altitude, pulmonary pressures, minuteventilation, shortness of breath, exercise tolerance, heart rate,transthoracic impedance, and heart sounds. Based on the parametricextraction, a composite CHF monitoring metric is computed by themonitoring system to evaluate and monitor the heart condition andworsening heart failure in CHF patients.

Upon wearing the textile-based harness (wearable device), the sensorspresent in the harness get placed in specific locations in the body. Thesensors acquire raw physiological signals and electrically transmit itto the SAU, which processes the signals and transmit them to themonitoring system for further processing and analysis. When a signalacquisition unit and a smart phone is powered on, the signal acquisitionunit and the smart phone are connected to each other wirelessly. A smartphone controls the signal acquisition unit by sending command to thesignal acquisition unit through wireless such as Bluetooth, Wi-Fi, orother wireless communication standards. Commands from the smart phone tothe acquisition unit include initializing the acquisition unit,requesting to send data to the smart phone for signal quality check atthe beginning stage of test, requesting start and stop test, andrequesting to upload stored data in the storage of the acquisition unitthrough wireless after the test is completed. In addition to communicatewith the acquisition unit, it sends log symptoms triggered by a patientto the portal or server.

Wearable sensor systems and devices are highly unobtrusive andbeneficial for home healthcare monitoring and provide freedom ofmovement. They are cost-effective, easy to use, compact, non-invasive,and simple yet efficient in operation. Long term monitoring is useful inmonitoring chronic diseases like CHF, and the wearable harness trulysupport non-invasive long-term monitoring. Monitoring, and evaluatingpatient diagnosed with CHF with one or more of the aforementionedphysiological signals and/or derived parameters through a wearable andwireless harness has numerous advantages including: enabling earlierintervention and diagnosis, enable earlier prediction of worsening heartcondition, enabling physicians to prescribe better medications, enablingbetter treatment and therapies to maximize the benefits, avoiding theneed for expensive and invasive implantable devices, enabling the wearerto carry on everyday activities, providing freedom of movement,comfortable to wear, replaceable and cost effective, and enablingremote, long-term, continuous and unobtrusive monitoring.

Wearable Device

A wearable textile-based harness, as shown in FIG. 1(a-d), comprises ofa horizontal band and a vertical band. FIGS. 1(a-b) show a harness withthe vertical band 12 connected to the horizontal band 10 at the front atxyphoid process location and on the back at a location 14 to the rightof back center (from the perspective of the wearer). FIGS. 1(c-d) show aharness with the vertical band 13 connected to the horizontal band 11 atthe front at xyphoid process location and on the back at a location 15to the left of back center (from the perspective of the wearer). Theharness footprint covers the key sensor positions for measurement ofbiopotential electrocardiogram (ECG), bioimpedance for impedancecardiography (ICG) and respiration tidal volume and heart sound. Thehorizontal band covers the horizontal plane of the xyphoid process andis an optimum location for measurement of ventricular heart activity,and lung air intake and lung fluid level. The vertical band covers theregion between the mid clavicle position and the 2-3 intercostal space,which is the optimal position for the sensors to detect the atrial heartactivity and to measure bioimpedance in combination with sensors placedat the xyphoid process level. The junction point of the horizontal andthe vertical band is an optimal location for measurement of S3 heartsound. The sound sensor faces the apex of the heart and can detect S3sound especially when the patient is in a left decubitus position. Thehorizontal band 10,11 wraps around the body in the thoracic cage region.The horizontal band passes over xyphoid process and thoracic cagebetween 5th and 6th ribs positions. The vertical band 12,13 wraps overthe shoulder like a satchel passing between shoulder muscle and deltoidmuscle. The vertical band is connected to the horizontal band in frontat the xyphoid process location and at the back on either side of theback-center 14,15 based on the requirements for compression. The widthof the band can be between 1 inch and 6 inches.

The position of the vertical and horizontal band covers the locations ofsensors for detection of ECG signals along the 2 different vectors (seeFIG. 4(b) vectors 1 and 2) to capture atrial and ventricular activity.The position also covers sensor locations for capturing hemodynamicactivity within the descending aorta as well as the lung filling cycle.The connection point of vertical and horizontal band covers the apexposition of the heart to capture S1, S2 and S3 heart sound using a soundsensor.

The horizontal and vertical bands are strapped around the thoracic cageand over the shoulder by using adjustable fasteners such as buckle(s) orVelcro. Preferably, the vertical band is always in a closed positionlike a shoulder strap, while the horizontal band has open ends. The userfastens the horizontal band around the thoracic cage with thefastener(s) and then slips the vertical band (strap) over the rightshoulder. The users can put the harness on and take the harness off bythemselves without any help, which enables them to use this device bythemselves in the comfort of their home. The size adjustable bands makethe harness suitable for users of wide range of sizes and it is genderagnostic. The buckles on the horizontal and vertical bands also allowfor adjustment of harness for different size subjects. The elasticity ofthe harness material allows for the sensors to get placed at the correctposition for all size users.

The bands (10-13) are made of elastomeric compression fabric materialthat has load-elongation curve for four test cycles as shown in FIG.2(a). This illustrates that the elastomeric material of the harnessmaintains its elasticity after repeated loading. The harness designexerts compressive force with the vertical and horizontal bands within adesired force range of 60-250 gf (gram-force) when the user wears theharness in order to effect reliable sensor measurement. FIG. 2(b) showsthe compressive force ranges in gram-force at each location of harnessduring different postures (static) and different movements (dynamic) asshown in FIG. 2(b). As shown in FIG. 2(c), the harness is divided into 5regions where the sensors are likely to be positioned: TOP 19(a) (on thevertical band), Left center 19(b), Right center 19(c), Left 19(d) andRight 19(e) (all on the front part of horizontal band).

The base fabric 17 of the harness bands is augmented by usingelastomeric material 16(b) (shore 00 30-50) at the location 18 fornanosensor(s) 16(a) that rise over the outer surface of the base fabric17 by 2-6mm as shown in FIG. 3. A non-elastomeric material 16(c), suchas a rip stop fabric, is preferably provided between the elastomericmaterial 16(b) and the base fabric 17, so that that the elastomericmaterial 16(b) is reinforced with 16(c) to ensure that the configuration16 does not bulge out toward base fabric 17. The nanosensor 16(a) isattached to 16(b) by thermally cured glues such as polyurethane basedadhesive films and silver loaded polyurethane based adhesive pastes.These bonded films are wash resistant. This configuration always pushesout the nanosensors towards the wearer's skin. This implementation isintended for better skin-sensor contact by compensating for differentskin contours and hold the sensor in place during movement or change inposture. The elastic fabric may, for example, be polyester withLYCRA/spandex/elastane, nylon with LYCRA/spandex/elastane, cotton polyrib, and the like. The fabric may have a variety of different weavessuch as plain, knitted or tricot. The elastomeric material may have aShore 00 hardness of 30-50, and be made of neoprene, EPDM (ethylenepropylene diene monomer), polyurethanes, and the like.

The measurement of ECG and ICG is done along 2 different vectors,illustrated in FIG. 4(b). Vector 1 runs diagonally across the rib cagefrom right shoulder to lower left side of the rib cage. This vector isconsistent with Lead II of ECG. Since one of the ECG sensors for thislead is above the heart and the other is below the heart, it can be usedfor monitoring the atrial activity (P wave) and ventricular activity(QRS complex and T wave). As shown in FIG. 4(a), the set of 4 sensors1,2,3,4 are placed along vector 1 such that sensors 1 and 2 are abovethe heart's position and sensor 3 and 4 are placed below the heart'slocation. Current applied between sensors 1 and 4 passes through theheart and descending aorta to take the path of least resistance and thepotential difference is picked up by sensors 2 and 3. Therefore,bioimpedance measured along this vector is affected by the volume ofblood being pumped by heart and passing through the descending aorta. Itis also affected by the lungs air volume. Accordingly, this bioimpedancesignal can be used to derive Impedance Cardiography (ICG) as firstderivative of bioimpedance. The respiration signal is the low frequencybase line sinusoid in the bioimpedance signal .The relative respirationtidal volume is obtained by measuring the peak amplitude in therespiration signal.

Vector 2 runs across the rib cage from lower right side to lower leftside of the rib cage. This vector uses sensors 6 and 7 for measurementof ECG. Since they are placed on either sides of the heart and below theheart, they can pick up ventricular activity (QRS complex and T wave)and in some cases atrial activity (Pwave). The set of 4 sensors 5,6,7,8are placed such that sensors 5 and 6 are on right side of the heart'sposition and sensors 7 and 8 are left side of the heat's position.Current applied between sensors 5 and 8 passes through the descendingaorta and the thoracic cage space at the lower level to take the path ofleast resistance and the potential difference is picked up by sensors 6and 7. Therefore, bioimpedance measured along this vector issignificantly affected by the lungs air volume. It is also affected byvolume of blood passing through the descending aorta. Accordingly, thisbioimpedance signal can be used to derive Impedance Cardiography (ICG)as first derivative of bioimpedance. The respiration signal is the lowfrequency base line sinusoid in the bioimpedance signal. The relativerespiration tidal volume is obtained by measuring the peak amplitude inthe respiration signal. Apart from the redundancy provided by thisvector, the bioimpedance baseline of this vector is also affected bywater retention in the lungs, which is a condition that may be prevalentin Congestive Heart Failure patients.

The configuration of sensors as shown in FIG. 4(a,b) give impedancecardiography (ICG) and electrocardiography ECG along vectors 1 and 2(FIG. 4(b)) with respect to wearer's body. Electrical current (Up to 5mA) is passed between Nanosensors 1 and 4 (FIG. 4(a)) through the bodyalong vector 1 and Nanosensors 2 and 3 measure change in potential toobtain ICG Vector 1. ECG Vector 1 is the voltage drop (change inpotential) across nanosensors 2 and 3 measured passively (e.g., withoutapplication of current). Current (Up to 5 mA) is passed betweenNanosensors 5 and 8 through the body along vector 2 and Nanosensors 6and 7 measure change in potential to obtain ICG Vector 2. ECG Vector 2is the voltage drop (change in potential) across nanosensors 6 and 7measured passively (e.g., without application of current). Current isapplied as a modulated signal, such as a square wave, and thecorresponding change in potential is measured by nanosensors andimpedance ZO is calculated for ICG. The same nanosensors 2,3,6,7,measuring change in potential, also passively measure ECG along therespective vector (e.g. without the application of current). Themeasured impedance (Z0) is processed to extract respiration rate. Thefirst derivative of impedance (Z0) gives the dZ/dt. The dZ/dt ispresented as ICG and respiration is extracted from Z0 as shown in FIG.5. The respiration signal is the low frequency base line sinusoid in thebioimpedance signal (Z0). The relative respiration tidal volume(discussed below) is obtained by measuring the peak amplitude in therespiration signal. The ECG and ICG from vectors 1 and 2 are shown inrows 1,2 and 4,5 respectively. Respiration, in row 6, is derived fromvector 2 ICG. The activity data in row 7 of FIG. 5 is derived fromsignals from inertial measurement unit (IMU) data shown in FIG. 6.

A heart sound signal is shown in row 3 of FIG. 5. A heart sound sensorsystem 9 is used in the detection of heart sound. This heart soundsensor can either be a MEMS, piezoelectric, condenser and acousticmicrophone, or accelerometer-based sensing element. The heart soundsensor is packaged in a moisture and dust proof flexible enclosure, sothat it can be protected from body sweat and dead skin and, so that itcan withstand wash cycles. It is positioned such that it is orientedtowards the lower apex of the heart. The heart sound sensor ispreferably mounted on a sound absorbent material such as neoprene rubberfoam with micro air-cavities. The foam mount has void space to house theheart sound sensor. An inertial measurement unite (IMU) is mounted onthe harness at or near the same location as heart sound sensor. The IMUmeasures linear acceleration, angular rotation, and magnetic fieldvectors to detect movement and rotation shown in FIG. 6. It also tracksthe orientation of the wearer's body. IMU's are commercially availablefrom a variety of manufacturers, including but not limited to AnalogDevices Inc, Microchip Technology, Honeywell Sensing and ProductivitySolutions, Maxim Integrated, TDK Invensense, etc.

FIG. 7(a-d) shows a diagram of a sensor system on a textile basedwearable substrate used for detection of ICG, ECG, respiration rate,heart sound and actigraphy. The substrate 20, 21 (FIG. 7(a)) can be awearable form factor such as patch, harness or garment. In the contextof FIG. 1, the horizontal band 10/11 and vertical band 12/13 are made ofthe substrate 20/21, with sensors on side 20 facing the skin. In otherwords, in the context of FIG. 3, the substrate 20/21 corresponds toelastic fabric 17. Alternatively, the substrate 20/21 could be glued,sewed, or otherwise secured to the bands 10/11, and 12/13. The sensorsystem is comprised of one or more nanosensors, heart sound sensor andIMU on the side 20 in contact with wearer's skin. The sensorshapes/patterns may be circular, oval 22 (FIG. 7(c)), clover leaf 23(FIG. 7(d)) or fractal carpet of sensors which are connected indifferent configurations to optimize signal detection. Such shapes canbe used to achieve better contact on contoured interface such as fabrictouching the human body. As one or ordinary skill in the art willappreciate, a fractal carpet is array of sensors arranged in a repeatedgeometric pattern, where the individual sensors can be of any shape(circle, square etc.).

Preferably, side 20 also incorporates the conductive tracks 27, 28 andconnectors 29 (FIG. 7(b)). Accordingly, in the context of FIG. 3,conductive tracks are on skin-facing side of fabric 17, and areconnected through layers 16(b) and 16(c) to sensor 16(a) havingnanosensors 22/23. Nanosensors 22 or 23 are printed nanosensors that areused in sensing ICG, ECG and respiration signals. The nanosensor surfacehas vertically standing nanofilaments that form a uniform coverage 24 onthe sensor surface or form hierarchical structures 25 (FIG. 7(d)). Oneor more nanosensors 22 or 23 are printed and/or bonded onto thesubstrate 20 in an array. Conductive tracks 27, 28 are printed in or onthe fabric 26, and are used to relay the sensed signal from the sensorto electronics 31 through a connector 29. The connection between thefabric and electronics can be established by directly attaching theconnector 29 and a connector 30 together or through conductive wires 32.Signals are received in electronics 31 and are processed and stored ortransmitted wirelessly to a receiver or cloud network for remotemonitoring. The electronics 31 can also be connected to computingequipment via cables 33 to monitor or analyze the signals.

The nanosensors are textile-based sensors. Two/three component yarn,which has polymer nanofibers embedded in a matrix of another polymer,can be used in fabrication of the nanosensor 22,23. Embedded nanofiberscan be released by dissolving the matrix polymer. Vertically standingnanofilaments on fabric can be obtained by electrostatic or pneumaticdeposition of two/three component fibers followed by dissolving thematrix polymer. The two/three component fibers have static charge thatis imparted to them by chemical treatment of the fiber surface. Thesefibers respond to externally applied electrostatic field. The externallyapplied static field drives the fibers to adhesive coated textilesubstrate and makes them stand upright. The deposition is site specificbecause it is defined by the pattern of adhesive printed on fabric 20that helps fibers adhere to fabric surface. The matrix polymer is thendissolved to expose the embedded nanofilaments. These nanofilaments arecoated with conductive material to make them nanosensors.

The deposition and coating processes can be done in two ways: a) withnanostructured fibers not coated with conductive material are depositedon the textile substrate and coated with conductive material later, forexample, by an electroless plating process or b) with nanostructuredfibers pre-coated with conductive material such as silver, gold,platinum, polyaniline, polypyrrole, poly(3,4-ethylenedioxythiophene) andrendered conductive and depositing these fibers on the textilesubstrate. For example, precoated nanostructured filaments can beprepared prior to the deposition process by batch spray coating thefilaments, or by coating vertically freestanding nanostructuredfilaments on a dissolvable substrate followed by release of thevertically freestanding nanofilaments by dissolving the substrate.

The nanosensors and methods for manufacturing the same are described infurther detail in US 2018/0080126, 2017/0226643, and 2016/0222539, eachentitled Large Scale Manufacturing of Hybrid Nanostructured TextileSensors, US 2013/0211208, entitled Smart Materials, Dry Textile Sensors,and Electronics Integration in Clothing, Bed Sheets, and Pillow Casesfor Neurological, Cardiac and/or Pulmonary Monitoring, US 2017/0225447,entitled Roll-To-Roll Large Scale Manufacturing and ElectronicsIntegration Process of Wireless Nanosensor Systems for Human HealthMonitoring, US 20130281815, and US 2013/0281795, each entitled WearableRemote Electrophysiological Monitoring System, the entire disclosures ofwhich are hereby incorporated by reference in their entirety.

Electronics

FIG. 8 illustrates data flow of the CHF management system. When a signalacquisition unit 40 and a smart phone 50 is powered on, the signalacquisition unit and the smart phone are connected to each otherwirelessly. The smart phone controls the signal acquisition unit bysending command to the signal acquisition unit wirelessly such asBluetooth, Wi-Fi, or other wireless communication standards. Commandsfrom the smart phone to the acquisition unit include initializing theacquisition unit, requesting to send data to the smart phone for signalquality check at the beginning stage of test, requesting start and stoptest, and requesting to upload stored data in the storage of theacquisition unit wirelessly after the test is completed. In addition tocommunicating with the acquisition unit, the smart phone 50 it sends logsymptoms triggered by a patient to the portal or server. Once the testis started, the signal acquisition unit acquires and processes signalsfrom sensors. The processed signals are stored to the storage such as aSD card or flash memory. Once the test is completed, the stored data aretransferred and uploaded to the server or the portal 60 through wiredconnection or wireless connection.

FIG. 9 illustrates a block diagram of the signal acquisition unit 40.The signal acquisition unit (SAU) is designed to be suitable forintegration into the harness. Although this is preferred, the SAU couldalso be located separately or on a different garment. An Analog FrontEnd circuit for impedances 41 can have multiple modulation anddemodulation circuits to measure multiple impedance vectors. An AnalogFront End circuit for ECGs 42 can have multiple amplifier and filtercircuits to measure multiple ECG signals. An Analog Front End circuitfor Heart sound 43 can also have multiple amplifier and filter circuitsto sense the multiple heart sounds and use them to signal processingsuch as noise cancellation. The front-end circuit for impedance 41, thefront-end circuit for ECGs 42, the front-end circuit for heart sound 43,and the front-end circuit for IMU are connected to the processing unit45 (e.g. a microprocessor) to allow processing of the signals. Thefront-end circuit for IMU 44 detects a patient's posture and activity.This front-end includes amplifiers and filters to process the signalsfrom IMU. The processed signals are used to detect patients posture andactivity. The IMU may also be used for compensation of the signalsaffected by the patient's movements. A power supply 47 is to provide theproper voltages and power to each circuit from a battery to power up theacquisition unit 40.

Such Analog Front End circuits, which include amplifiers, filters, andassociated circuitry for converting analog sensor signals into digitalsignals which can processed by a microprocessor are well known in theart and are commercially available from a variety of sources, includingTexas Instruments, Microchip Technology, Samsung Semiconductor,Panasonic Electronics Components, STMicroelectronics, MicrosemiCorporation, NXP USA Inc, Analog Devices, etc.

The SAU 40 also includes a memory or local storage medium 46 for storingthe code or software for operating the microprocessor 45 and for storingdata, including data received from the sensors.

The SAU 40 also includes a wireless module for effecting wirelesscommunication with the smart phone 50 and web server 60 via Bluetooth,Wi-Fi, or other wireless communication standards. Such wireless modulesare well known in the art and are commercially available from a varietyof sources, including Texas Instruments, Microchip Technology, SamsungSemiconductor, Panasonic Electronics Components, Abracon LLC, MurataElectronics North America, etc.

Software

The SAU 40 has a storage medium 45 that contains microprocessor ormicrocontroller executable code 401 that performs the steps of capturingand converting the signals from the sensors and IMU into machinereadable digitized data. The code 401 also creates arrays of digitizeddata that are stored in a traditional file system for subsequentretrieval in local storage medium 46. This storage medium isnon-volatile memory that can be erased and programmed as needed. Thecode 401 also transmits and receives data and commands to and from aninternet connected database service that resides in a remote physicaldatabase server such as web server 60, and to and from smart phone 50,through wireless module 48. The code 401 can communicate with the serverdirectly and transfer the acquired data for a patient if a smart phone50 is not within wireless communication range of the signal acquisitionunit 40.

FIGS. 10(a) and 10(b) show illustrative steps of code 401, in furtherdetail.

Code 401 preferably captures and digitizes data from several channelsthat can have different sampling frequency requirements (step 401-1). Inthis regard, the code 401 can serialize the digitized data and generatepackets on a per second basis or at a frequency equivalent to the lowestsampling frequency (step 401-2 and 401-3). An exemplary implementationof serialization for a set of signals sampled at different frequenciesis provided in FIG. 11. The lowest sampling rate here is 50 Hz.Therefore, a composite packet as described in Figure is generated every20 milliseconds, encrypted and stored in the SAU.

Code 401 also performs feature extraction including: calculaterespiratory rate from impedance Z0, calculate ICG as first derivative ofimpedance Z0, calculate heart rate from ECG, calculate peak-to-peakchange in amplitude of impedance indicating rate of respiration andchange in chest volume due to inhalation (step 401-3). These extractedfeatures are then encrypted (401-5) and stored (401-6) in memory 46, forlater transmission to the smart phone 50 and/or web server 60 (401-7).It should be noted that although the feature extraction is preferablyperformed on the SAU 40, it is also possible to instead perform thesesteps on smart phone 50 or web server 60.

The smart phone 50 includes a microcontroller or microprocessor and astorage medium that contains microcontroller or microprocessorexecutable code 501. FIGS. 10(a) show illustrative steps for the code501. The code 501 can perform the functions related to the command andinterface functions in FIG. 8. The command responses may include but notlimited to the following list of commands and their associated responsesand descriptions.

TABLE 1 Command Command Name code(HEX) Command DescriptionACC_FileDuration 0x00 This command is used to set the amount of data tobe stored in a single file. ACC_StatusVariable 0x01 This command is usedto query the module for its current status. ACC_StartAcquisitionRequest0x02 This command will start the signal data acquisition from the Analogfront End. The acquired data is encrypted and stored on the SD card.ACC_RealTimeClockSet 0x03 This command is used to set the Real TimeClock and Calendar values on the Microcontroller. This operation needsto be done to synchronize the time between the smart device 20 and thetime included in the data files that are captured by 10.ACC_FileTransferRequest 0x04 This command is used to request completedfiles from the module. The module will search for the requested file andstart transferring the contents of the file from the Signal acquisitionunit ACC_RealTimeReadRequest 0x05 This command returns the value of theReal-time clock and calendar on the SAU 10. ACC_StopAcquisitionSleep0x06 This command instructs the module to go to sleep mode where allfunctions of the SAU are suspended. ACC_RealTimeStreamRequest* 0x07Streams the acquired data to the smart device in a specified formatACC_SetEncryptionKey 0x08 This command is used to set the encryption keyon the SAU at the beginning of the test. ACC_CurrentFileNumber 0x09 Thiscommand is used to query the module to determine the current filenumber. ACC_DeviceID 0x0A This command is read the device ID informationACC_FileSize 0x0B This command is used to determine the number of bytesin each file. ACC_FileTransferCancel 0x0C This command is used to cancelan ongoing file transfer. ACC_SendKeepAlive 0x0D This command is used torequest the SAU to send message beacons that serve as pings to keep thesmart device app active. ACC_DataSession 0x0E This command is used bythe Smart device to inform the SAU that a data connection is eitherstarted or is about to terminate. ACC_GetGPSlocation 0x0F This commandis used by the SAU to inquire the smart device and retrieve GPS locationincluding altitude from a GPS service on the smart device.

Using the commands above, the code 501 sends and retrieves data from theSAU 40. The commands above were created following a standard programmingdesign pattern known as command pattern known to those skilled in theart.

The code 501 also stores and accesses data on the local storage 502 inthe smart phone 502, including, for example, storing data received fromthe SAU. Code 501 can further communicate with the operating system code503 in smart phone 50 regarding the availability of an internetconnection that will allow communication to web services, and codes 501,503 effect uploading of data to the web server 60. The code in 501further communicates with a user interface and data managing softwaremodule 504. The interfaces between the patient or end user and the smartphone are implemented by this module.

The Web server/portal 60 is implemented as 2 services that work intandem, in an asynchronous manner. The web server 60 includes one ormore processors, memory, and software code as described below. The database services code 603 are responsible for collecting the data acquiredby the SAU, received either directly from the SAU 401 or through thesmart phone software code 501, 503. The database services code 603 routethe data to a secure cloud storage database 601 that is capable ofauto-scaling to meet increased demands as needed. As soon as new datafiles are available in database 601, queue processor code 605 processthe data files. Queue processor code 605 may include, but is not limitedto performing the following steps:

-   1. DecrypT the encrypted data from database 601 into unencrypted    data.-   2. Parse of the unencrypted (raw) data to separate them into    individual channels of physiological data;-   3. perform any needed data type and format conversions to allow for    further processing, including converting digitized recordings into    physical values such as voltage and impedance.-   4. perform calculation, extraction, and pattern recognition to    effect the determination of parameters/features listed in the    following table:

TABLE 2 Signal from which Derivation of parameter is Significance/ Nameof Parameter/feature parameter/feature extracted/computed ConclusionAtrial Electrical Activity Duration and amplitude ECG vector(s),Indicative of of P wave of ECG anomalies if present waveform in theatrial chambers of the heart Ventricular Electrical Activity Durationand amplitude ECG vector(s) Indicative of of QRS wave of ECG anomaliesif present waveform in the ventricular chambers of the heart PR intervalor Atrio-ventricular Time elapsed between P ECG vector(s) Time taken foratrial conduction interval wave and R wave impulse to reach theoccurrence in an ECG ventricle QRS measures Amplitude, duration and ECGvector(s) Indicative of axis of QRS waves of anomalies if present ECG.in the ventricular chambers of the heart ST-T wave measures ST segmentamplitude, ECG vector(s) Indicative of duration and slope in anomaliesif present ECG waveform in the relaxation of heart muscles after a beatPatient Activity Score Measure of physical Actigraphy - pattern ofIndicative of activity performed by changes in acceleration willingnessto be patient like walking, from a 3-axis active. climbing stairs ormore accelerometer, from IMU intense exercise Posture Measure of theabsolute Actigraphy - IMU has a a preference for posture maintained3-axis accelerometer that reclined instead of provides orientation withsupine is indicative of respect to gravity. fluid accumulation in thelungs. Cardiac Output Measure of the volume ICG vector(s) - Product ofMeasure of the of blood pumped from Area under the curve of heart'spumping the heart in a minute. It ICG waveform following efficiency isthe product of the the occurrence of a R peak volume of blood in thesimultaneously pumped out be the left acquired ECG, and heart ventricleof the heart rate as 60 times the and the heart rate. inverse of timeinterval between R peaks in the ECG waveform. Stroke Volume Measure ofvolume of ICG vector(s) - Area under Measure of the heart pumped fromthe the curve of ICG waveform heart's pumping ventricle of the heart.following the occurrence efficiency of a R peak in the simultaneouslyacquired ECG. Cardio-vascular Pressures Measure of the ICG vector(s) -Slope of the Indicative of the maximum pressure in peak followingcardiac health of the vascular the blood vessels contraction isinversely system and risk following a heart muscle proportional to theblood factors such as contraction that causes flow pulse velocity, whichchronic hypertension. blood flow and pressure is proportional tovascular between consecutive pressure. contractions. Patient GeographicLocation and Global Positioning Acquired from Indicates whether AltitudeSatellite (GPS) location SmartDevice using a patient is exposed to ofthe patient from the command-response high altitude patient's smartdevice. interface - A GPS module conditions, or travel. is present inall smartdevices. This module can be interrogated to get currentlocation and altitude. Pulmonary Measures Pulmonary measures ICGvector(s) - The low Indicative of the lung include tidal volume -frequency baseline function of the volume of air inhaled or variation ofimpedance is patient and whether exhaled during normal extracted asrespiratory the patient is breathing, and rate of signal using filterssuch as experiencing breathing, whether the a median filter. Impedanceshortness of breath. patient is experiencing increases with inhalationshortness of breath and lowers with wherein the respiratory exhalation.rate is high, but the volume of air displaced from the lungs is low.Minute Ventilation Measure of the amount ICG vector(s) - It is theIndicative of the lung of air displaced by the product of the tidalfunction of the lungs in a minute. volume from pulmonary patient andwhether measures and the the patient is respiratory rate. experiencingshortness of breath. Shortness of Breath Measure of the amount ICGvector(s) - from Shortness of breath is of air inhaled or exhaledcalculation of minute a direct indication of and rate of respiration.volume and respiratory worsening heart rate. failure leading tohospitalization. Exercise Tolerance Measures the changes in ECG and ICGvector(s) - Lowering of exercise heart rate and heart rate andrespiration tolerance is a leading respiration while are derived fromthe indicator of performing activities like inverse of the RR intervalsworsening heart a 6-minute walk from ECG, and median failure. filteredimpedance curve. Heart Rate Measures the total ECG vector(s) - Derivedas Elevated heart rate number of heart beats number of R peaks presentsuggests that the per minute within a one-minute time heart is unable towindow output sufficient volume of blood during a single cardiac cycleHeart Rhythm Measures the regularity ECG vector(s) Irregular heart beatof the heartbeat. indicates that there are underlying abnormalities withthe electrical activity of the heart. Transthoracic impedance Measuresthe electrical ICG vector(s) Thoracic impedance impedance of the thoraxwill be lower in or chest of the patient. patients with fluidaccumulation. This is a predictor of impending hospital admission due toshortness of breath.

-   5. Perform pattern recognition tasks on any features extracted by    the step 4 above to generate conclusions on the patient or end users    current CHF burden, prognosis and treatment recommendations.    Examples of such conclusions are set forth in Table 2.

Queue processor code 605 can further send an email to the appropriatephysician based on any anomalies detected in the measured data such asdeviations from thresholds that are set by the physician for eachparameter that is monitored in a CHF patient.

After the data files have been processed by code 605, the resultingmeta-data, features or parameters are stored in a database 604. Thedatabases 601 and 604 may be combined in a single database in a mannerthat is known to any person skilled in database management systems.

The web portal front end 602 is responsible for the management of theprocessed data and generating a user interface wherein the data ispresented in a human readable form to a physician. Front end code 602accesses the data that has been processed by code 605 through thedatabase services in code 603.

FIGS. 12-15 illustrate an exemplary implementation of user interfacethat is accessible to an end user or patient while setting up a SAU forCHF monitoring. FIG. 12 is a log in screen for accessing web portal.FIG. 13 shows a dashboard screen for user “Dr. Jay”, which shows, foreach patient of Dr. Jay being monitored, review status, patient name,patient MRN, date monitoring commenced, date of most recent data,compliance percentage, and priority. FIG. 14(a) illustrates a screen forinputting patient information, including, name, address, date of birth,doctor, insurance carrier, email, and priority. It also includes abutton for initiating synching of the electronic medical record (EMR) ofthe patient. FIG. 14(b) is a screen in which the user can elect to setup a connection to the SAU and smartphone. If the user selects yes inFIG. 14(b), a code is displayed as shown in FIG. 14(c). As a person ofordinary skill in the art will appreciate, use of such codes is a wellknown method of set up connection to a remote device such as a smartphone. To connect the device (eg. Smart phone), the user enters theinformation on the screens shown in FIG. 15(a)-(c) from a “simplesense”app on the smartphone, including username/password and then the codefrom FIG. 14(c). FIG. 16 shows a screen which confirms that thesmartphone is connected to the SAU and to the server. The connection canbe managed through the Bluetooth connection manager on the smartphoneapp and exchange of a handshake message over standard RepresentationalState Transfer (REST) or other Application Programming Interface (API)known to those skilled in the art. If the user selects record (FIG. 17a), then the smart phone 50 will instruct the SAU 40 to begin recordingthrough code 504 and then data will be acquired using code 501 (FIG.17(b), FIG. 18(a)) , and then uploaded (FIG. 18(b)) to the databaseservices code 603 in web server 60.

FIG. 19 shows the data display for one of Dr. Jay's patients, includingthe patient name and data from the EMR on the left, and then on theright the data from the harness discussed previously with respect toFIG. 6. Also shown on the left of the display is the “simple sense”score of 24. FIG. 20 is a screen showing the simple sense score overtime. The SimpleSense score is a weighted sum of a combination ofseveral features listed in Table 2. The score is a probabilisticpredictor that indicates the likelihood of impending hospital emergencyadmission for a patient with heart failure due to worsening heartfailure symptoms.

FIG. 21 shows a patient setting screen which allows Dr Jay to set alertsfor the patient, including stroke volume alert, ratio of respirationrate to relative tidal volume alert, trans-thoratic impedance alert,presence of S3 sounds alert, level of activity alert, level of activityalert, change in simple sense alert. Stroke volume is a direct measureof the amount of blood the heart is able to pump in one cardiac cyclewith is a metric used to assess heart failure patients. Ratio ofrespiration rate to relative tidal volume is a measure of shortness ofbreath. Presence of S3 heart sounds indicates that there is resistanceto the filling of the left ventricle, which in turn lowers the strokevolume. Level of activity changes are an indirect indicator of thepatient's exercise tolerance. Change in Simplesense is an indicator ofthe rapidity of change in the patient's condition.

In the preceding specification, the invention has been described withreference to specific exemplary embodiments and examples thereof. Itwill, however, be evident that various modifications and changes may bemade thereto without departing from the broader spirit and scope of theinvention as set forth in the claims that follow. The specification anddrawings are accordingly to be regarded in an illustrative manner ratherthan a restrictive sense.

Obvious variants of the disclosed embodiments are within the scope ofthe description and the claims that follow.

All references cited herein, as well as text appearing in the figuresand tables, are hereby incorporated by reference in their entirety forall purposes to the same extent as if each were so individually denoted.

1.-20. (canceled)
 21. A wearable, textile-based, adjustable elastichorizontal band wherein: the band is configured for wrapping proximateto a body portion of a wearer around the thoracic cage region and forpassing over a xyphoid process and a thoracic cage between 5th and 6thribs positions; a plurality of sensors configured for location along theband, wherein the plurality of sensors include a first and second sensorconfigured for location to the right of the heart of the wearer betweenthe lower-right of the thoracic cage between 5th and 6th ribs positionsand a third and fourth sensor configured for location to the left of theheart of the wearer between the lower-left of the thoracic cage between5th and 6th ribs positions, wherein the first sensor is configured forapproximate location below a right armpit and the third sensor isconfigured for approximate location below a left armpit and wherein thesecond sensor is located downward and to the heart side of the firstsensor and the fourth sensor is located downward and to the heart sideof the third sensor.
 22. The band of claim 21, wherein the first,second, third and fourth sensors are configured for location on a frontside of the band.
 23. The band of claim 21, wherein the first, second,third and fourth sensors are configured for location on a back side ofthe band.
 24. The band of claim 21, wherein the band is adjustable viafasteners.
 25. The band of claim 21, wherein band is made of an elasticfabric, and wherein each of the plurality of sensors are located atsensor locations on the elastic fabric, and wherein, at one or more ofthe sensor locations, a non-elastic material is fixed on the elasticfabric, an elastomeric material is fixed on the non-elastic material,and one or more of the sensors is fixed on the elastomeric material. 26.The band of claim 21, wherein the plurality of sensors include at leastone textile based nanosensor comprising vertically standingnanofilaments.
 27. The band of claim 21, wherein upon wearing the band,the first and second plurality of sensors are placed in contact withskin of wearer with a sensor-skin pressure in the range of 60 to 250gram-force.
 28. A sleep disorder management system comprising: awearable, textile-based, adjustable elastic horizontal band wherein theband is configured for wrapping proximate to a body portion of a weareraround the thoracic cage region and for passing over a xyphoid processand a thoracic cage between 5th and 6th ribs positions; a plurality ofsensors configured for location along the band, wherein the plurality ofsensors include a first and second sensor configured for location to theright of the heart of the wearer between the lower-right of the thoraciccage between 5th and 6th ribs positions and a third and fourth sensorconfigured for location to the left of the heart of the wearer betweenthe lower-left of the thoracic cage between 5th and 6th ribs positions,wherein the first sensor is configured for approximate location below aright armpit and the third sensor is configured for approximate locationbelow a left armpit and wherein the second sensor is located downwardand to the heart side of the first sensor and the fourth sensor islocated downward and to the heart side of the third sensor; a signalacquisition unit including an analog front end circuit, a processor, awireless module, and a power supply, the SAU receiving signals from theplurality of sensors, generating, from the signals, an ECG signal and anICG signal, and wirelessly transmitting at least the ECG signal and theICG signal to a remote computing device.
 29. The system of claim 28,further comprising the remote computing device, the remote computingdevice including a processor and computer readable media having storedthereon computer executable process steps operative to control theprocessor to display on a display screen a graph of the ICG and ECGsignals as a function of time
 30. The system of claim 28, wherein theplurality of sensors include at least one textile based nanosensorcomprising vertically standing nanofilaments.
 31. The system of claim28, wherein at least one IMU is used to measure sleeping position,activity and posture.
 32. A method of detecting changes in patterns ofbreathing associated with sleep disordered breathing comprising:providing a wearable, textile-based, adjustable elastic horizontal band,wherein when worn by the human, the band wraps proximate to a bodyportion of the human around the thoracic cage region and passes over axyphoid process and a thoracic cage between 5th and 6th ribs positions,said band including a plurality of sensors located along the band,wherein the plurality of sensors include a first and second sensorlocated on a front side of the band to the right of the heart of thehuman between the lower-right of the thoracic cage between 5th and 6thribs positions and a third and fourth sensor located on the front sideof the band to the left of the heart of the human between the lower-leftof the thoracic cage between 5th and 6th ribs positions, wherein thesecond sensor is located downward and to the heart side of the firstsensor and the fourth sensor is located downward and to the heart sideof the third sensor and wherein the first sensor is configured forapproximate location below a right armpit and the third sensor isconfigured for approximate location below a left armpit, wherein uponwearing the textile-based band, the plurality of sensors are placed incontact with skin of the human; and measuring simultaneously therespiration and ECG of the human to detect changes in patterns ofbreathing associated with sleep disordered breathing.
 33. The method ofclaim 32, further comprising displaying on a display screen a graph ofthe ECG signal and respiration as a function of time.
 34. The method ofclaim 32, further comprising generating a plurality of parameters fromthe ECG and ICG vectors, including: atrial electrical activity from atleast one of the ECG vectors; ventricular electrical activity from atleast one of the ECG vectors; PR interval of atrio-ventricularconduction interval from at least one of the ECG vectors; QRS measuresfrom at least one of the ECG vectors; ST-T measures from at least one ofthe ECG vectors; cardiac output from at least one of the ICG vectors;stroke volume from at least one of the ICG vectors; cardio-vascularpressures from at least one of the ICG vectors; pulmonary pressures fromat least one of the ICG vectors; minute ventilation from at least one ofthe ICG vectors; shortness of breath from at least one of the ICGvectors; exercise tolerance from at least one of the ECG and ICGvectors; heart rate from at least one of the ECG vectors; heart rhythmfrom at least one of the ECG vectors; transthoracic impedance from atleast one of the ICG vectors; and ejection fraction from at least one ofthe ICG vectors.
 35. A method of determining sleep state or wakefulnessusing the combination of posture, activity, respiration, and heart rateas a function of time in a human, comprising: providing a wearable,textile-based, adjustable elastic horizontal band, wherein when worn bythe human, the band wraps proximate to a body portion of the humanaround the thoracic cage region and passes over a xyphoid process and athoracic cage between 5th and 6th ribs positions, said band including aplurality of sensors located along the band, wherein the plurality ofsensors include a first and second sensor located on a front side of theband to the right of the heart of the human between the lower-right ofthe thoracic cage between 5th and 6th ribs positions and a third andfourth sensor located on the front side of the band to the left of theheart of the human between the lower-left of the thoracic cage between5th and 6th ribs positions, wherein the second sensor is locateddownward and to the heart side of the first sensor and the fourth sensoris located downward and to the heart side of the third sensor andwherein the first sensor is configured for approximate location below aright armpit and the third sensor is configured for approximate locationbelow a left armpit, wherein upon wearing the textile-based band, theplurality of sensors are placed in contact with skin of the human; andmeasuring simultaneously the respiration and ECG, posture and activityof the human to detect changes in patterns of breathing, all as afunction of time, to determine sleep state or wakefulness.
 36. Themethod of claim 35, further comprising displaying on a display screen agraph of the ECG signal, respiration, posture and activity as a functionof time.
 37. The method of claim 35, further comprising generating aplurality of parameters from the ECG and ICG vectors, including: atrialelectrical activity from at least one of the ECG vectors; ventricularelectrical activity from at least one of the ECG vectors; PR interval ofatrio-ventricular conduction interval from at least one of the ECGvectors; QRS measures from at least one of the ECG vectors; ST-Tmeasures from at least one of the ECG vectors; cardiac output from atleast one of the ICG vectors; stroke volume from at least one of the ICGvectors; cardio-vascular pressures from at least one of the ICG vectors;pulmonary pressures from at least one of the ICG vectors; minuteventilation from at least one of the ICG vectors; shortness of breathfrom at least one of the ICG vectors; exercise tolerance from at leastone of the ECG and ICG vectors; heart rate from at least one of the ECGvectors; heart rhythm from at least one of the ECG vectors;transthoracic impedance from at least one of the ICG vectors; andejection fraction from at least one of the ICG vectors.
 38. The methodof claim 32, wherein the sleep disordered breathing is selected from thegroup consisting of central and/or obstructive sleep apnea, hypopnea,and arousal due to apnea events in a human,